At Rhoda AI, we're building the full-stack foundation for the next generation of humanoid robots — from high-performance, software-defined hardware to the foundational models and video world models that control it. Our robots are designed to be generalists capable of operating in complex, real-world environments and handling scenarios unseen in training. We work at the intersection of large-scale learning, robotics, and systems, with a research team that includes researchers from Stanford, Berkeley, Harvard, and beyond. We're not building a feature; we're building a new computing platform for physical work — and with over $400M raised, we're investing aggressively in the R&D, hardware development, and manufacturing scale-up to make that a reality.

We're looking for a Robot Control Engineer to develop and maintain the control systems that run on our humanoid robots. You'll own the software that connects hardware to behavior — from low-level control loops and actuator interfaces to state estimation and real-world deployment.

What You'll Do

• Develop and maintain onboard control software including control loops, state estimation, and actuator interfaces

• Implement and tune motion planning and control systems — including whole-body control, trajectory optimization, or model predictive control

• Collaborate with the AI/ML team to integrate learned control policies onto real hardware reliably and efficiently

• Contribute to system reliability, fault detection, and recovery logic for robust real-world operation

• Work directly with prototype hardware, debugging discrepancies between simulated and real behavior and iterating on both

• Support bring-up and field testing of new hardware revisions

What We're Looking For

• 4+ years of experience building control software for robotic systems or a closely related field

• Strong software engineering fundamentals in C++, Python, or Rust

• Hands-on experience with core robotics control: motion planning, control loops, state estimation, or actuator interfaces

• Experience with ROS/ROS2 or similar robotics middleware in production or research contexts

• Ability to debug across the full stack — from driver-level issues to control behavior on live hardware

• Comfort working directly with physical hardware in fast-moving, ambiguous environments

Nice to Have (But Not Required)

• Background in whole-body control, trajectory optimization, or model predictive control

• Experience building sim-to-real pipelines for reinforcement learning or imitation learning policy training

• Familiarity with humanoid or legged robot platforms and the unique modeling challenges they present

• Exposure to learned perception or control models and their integration into real-time robot stacks

• Prior work on early-stage hardware programs (prototype or pre-production robots)

Why This Role

• Your code runs on the robot — the control software you write has a direct, physical impact on what our humanoids can do in the real world

• Work at the boundary of hardware and AI, integrating state-of-the-art control and learned policies onto real robotic systems

• High ownership in a small, fast-moving team where your contributions shape how the next generation of humanoid robots operate in production